Update app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import openai
+
+# Load the solar data CSV file
+df = pd.read_csv('solar_data_india_2024.csv')
+
+# Set up the Gemini API (replace with your actual API key)
+openai.api_key = 'your_gemini_api_key_here'
+
+# Function to get solar radiation and tariff based on user input location
+def get_state_data(state_name):
+    state_data = df[df['State'].str.contains(state_name, case=False)]
+    if state_data.empty:
+        return None
+    return state_data.iloc[0]
+
+# Function to estimate solar system size (in kW)
+def estimate_system_size(roof_size, ghi):
+    # Simple formula: 1 kW system needs about 10-12 sq meters of roof space
+    system_size = roof_size / 10  # in kW (assuming 10 sq meters = 1 kW)
+    estimated_output = ghi * system_size  # kWh per day
+    return system_size, estimated_output
+
+# Function to calculate cost, savings, and payback period
+def estimate_cost_and_savings(system_size, state_data, electricity_bill):
+    # Cost per kW (₹)
+    solar_cost_per_kw = state_data['Solar_Cost_per_kW (₹)']
+    # Total solar system cost
+    system_cost = system_size * solar_cost_per_kw
+    # Savings per month assuming 100% replacement of electricity bill
+    savings_per_month = electricity_bill
+    # Payback period in months
+    payback_period = system_cost / (savings_per_month * 12)
+    
+    return system_cost, savings_per_month, payback_period
+
+# Streamlit UI
+st.title("AI-based Solar Project Estimation Tool")
+
+# User input form
+st.sidebar.header("Enter Your Details")
+location = st.sidebar.text_input("Enter your city or state", "")
+roof_size = st.sidebar.number_input("Enter your roof size (in sq meters)", min_value=1)
+electricity_bill = st.sidebar.number_input("Enter your monthly electricity bill (₹)", min_value=0)
+
+if location and roof_size > 0 and electricity_bill >= 0:
+    # Fetch state data from the dataset
+    state_data = get_state_data(location)
+    if state_data is not None:
+        ghi = state_data['Avg_GHI (kWh/m²/day)']
+        
+        # Estimate solar system size and output
+        system_size, estimated_output = estimate_system_size(roof_size, ghi)
+        
+        # Estimate cost, savings, and payback period
+        system_cost, savings_per_month, payback_period = estimate_cost_and_savings(system_size, state_data, electricity_bill)
+        
+        # Display results
+        st.subheader("Estimated Solar System Details:")
+        st.write(f"**Location**: {location}")
+        st.write(f"**System Size**: {system_size:.2f} kW")
+        st.write(f"**Estimated Daily Output**: {estimated_output:.2f} kWh/day")
+        st.write(f"**Total System Cost**: ₹{system_cost:,.2f}")
+        st.write(f"**Monthly Savings**: ₹{savings_per_month:,.2f}")
+        st.write(f"**Payback Period**: {payback_period:.2f} years")
+        
+        # Plot savings and payback period
+        fig, ax = plt.subplots()
+        ax.bar(['Total System Cost', 'Monthly Savings', 'Payback Period'], 
+               [system_cost, savings_per_month, payback_period*12], color=['blue', 'green', 'orange'])
+        ax.set_ylabel("Amount (₹) / Time (years)")
+        ax.set_title("Solar System Estimation Breakdown")
+        st.pyplot(fig)
+        
+    else:
+        st.error("Sorry, the location entered does not match any available data.")
+else:
+    st.warning("Please fill out all fields to see your solar project estimate.")